A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks

被引:383
作者
Chine, W. [1 ]
Mellit, A. [1 ,2 ]
Lughi, V. [3 ]
Malek, A. [4 ]
Sulligoi, G. [3 ]
Pavan, A. Massi [3 ]
机构
[1] Univ Jijel, Fac Sci & Technol, Dept Elect, Renewable Energy Lab, POB 98, Ouled Aissa 18000, Jijel, Algeria
[2] Abdus Salam Int Ctr Theoret Phys ICTP, Str Costiera 11, I-34151 Trieste, Italy
[3] Univ Trieste, Dept Engn & Architecture, Via A Valerio 6-A, I-34127 Trieste, Italy
[4] Ctr Dev Energies Renouvelables, BP 62 Route Observ, Bouzareah 16340, Alger, Algeria
关键词
photovoltaics; Fault detection; Fault diagnosis; ANN; FPGA; ENERGY-PRODUCTION; MODULES; MISMATCH; IMPLEMENTATION; PERFORMANCE; OVERCURRENT; PROTECTION; LOSSES; PANELS;
D O I
10.1016/j.renene.2016.01.036
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This work proposes a novel fault diagnostic technique for photovoltaic systems based on Artificial Neural Networks (ANN). For a given set of working conditions - solar irradiance and photovoltaic (PV) module's temperature - a number of attributes such as current, voltage, and number of peaks in the current-voltage (I-V) characteristics of the PV strings are calculated using a simulation model. The simulated attributes are then compared with the ones obtained from the field measurements, leading to the identification of possible faulty operating conditions. Two different algorithms are then developed in order to isolate and identify eight different types of faults. The method has been validated using an experimental database of climatic and electrical parameters from a PV string installed at the Renewable Energy Laboratory (REL) of the University of Jijel (Algeria). The obtained results show that the proposed technique can accurately detect and classify the different faults occurring in a PV array. This work also shows the implementation of the developed method into a Field Programmable Gate Array (FPGA) using a Xilinx System Generator (XSG) and an Integrated Software Environment (ISE). (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:501 / 512
页数:12
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